Evidence map›Paper›PMID 40008391›Full record

ArticleCancer informatics2025

An Immunogenic Cell Death-Related Gene Signature Predicts the Prognosis and Immune Infiltration of Cervical Cancer.

Fangfang Sun, Yuanyuan Sun, Hui Tian

Abstract read
In one paragraph

Article in Cancer informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Fangfang SunDepartment of Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, P. R. China.
Yuanyuan SunDepartment of Translational Medicine Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, P. R. China.ORCID https://orcid.org/0000-0002-2843-739X
Hui TianSchool of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, Henan Province, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Immunogenic cell death (ICD) has been demonstrated to play a critical role in the development and progression of malignant tumors by modulating the anti-tumor immune response. However, its function in cervical cancer (CC) remains largely unexplored. In this study, we aimed to construct an ICD-related gene signature to predict patient prognosis and immune cell infiltration in CC. Methods: The gene expression profiles and clinical data of CC were downloaded from The Cancer Genome Alas (TCGA) and Gene Expression Omnibus (GEO) datasets, serving as the training and testing groups, respectively. An ICD-related gene signature was developed using the LASSO-Cox model. The expression levels of the associated ICD-related genes were evaluated using single-cell data, CC cell lines, and clinical samples in vitro. Results: Two ICD-associated subtypes (cluster 1 and cluster 2) were identified through consensus clustering. Patients classified into cluster 2 demonstrated higher levels of immune cell infiltration and exhibited a more favorable prognosis. Subsequently, an ICD-related gene signature comprising 3 genes (IL1B, IFNG, and FOXP3) was established for CC. Based on the median risk score, patients in both training and testing cohorts were segregated into high-risk and low-risk groups. Further analyses indicated that the estimated risk score functioned as an independent prognostic factor for CC and influenced immune cell abundance within the tumor microenvironment. The up-regulation of the identified ICD-related genes was further validated in CC cell lines and collected clinical samples. Conclusion: In summary, the stratification based on ICD-related genes demonstrated strong efficacy in predicting patient prognosis and immune cell infiltration, which also provides valuable new perspectives for the diagnosis and prognosis of CC.

Indexed as

BioinformaticsCervical cancerImmune infiltrationImmunogenic cell deathPrognosis

Identifiers

PMID40008391
PMCPMC11851768

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